A Dynamic Calibration and Compensation Method for the Asynchronous Time Between Two Inertial Navigation Systems

The carrier is usually equipped with two or more inertial navigation systems (INS) as redundant backup system configuration to improve reliability. In this case, information fusion from two or more INSs can achieve error detection and system state monitoring. However, due to the different information collection and process mechanism, the measurements from different INSs would not be synchronized, which would decrease the accuracy of the fusion algorithm and would cause wrong monitoring results. In this paper, a dynamic calibration and compensation method for the errors caused by time-gap between two asynchronous INSs is proposed. The causes of asynchronous time from different INSs are analyzed and the asynchronous time is modeled. Based on the model, an online estimation and compensation Kalman filter for asynchronous time is established. Using the difference of navigation information between two sets of INSs as measurements, the filter can estimate the asynchronous time between the two INSs. The simulation results show that the proposed method could achieve estimation accuracy of 0.027ms for the asynchronous time between different INSs, and the vehicle experimental results also demonstrate the effectiveness of the method.